Teaching

Organisation

The course presents the basic numerical and linear algebra techniques to solve mathematical problems that arise in computer science. The topics cover a wide range such as e.g.: basic concepts of scientific programming, solution of systems of linear equations and of nonlinear equations; interpolation and least-square approximation of data and functions; eigenvalues and eigenvectors computation; integration and differentiation and numerical optimization.

Content

Numerical methods to solve mathematical problems are central in many areas of computer science such as scientific computing, AI & machine learning, signal & image processing, computer vision, computer graphics & computational geometry, data analysis & mining, data visualization and more. At the core, numerical methods are often based on numerical linear algebra techniques.

In this course we will focus on this foundation and cover topics such as:

• Linear Equations in Linear Algebra
• Matrix Algebra
• Determinants
• Vector Spaces
• Eigenvalues and Eigenvectors
• Least Squares Problems
• Numerical Analysis

Literature

The lecture is based on the following textbook:

Linear Algebra and its Applications, by Lay, Lay and McDonald, 5th/Global Edition.

Lecture Material

The lecture material (slides, exercises etc.) will be available on the OLAT course website.

Participation and successfully passing the exercises during the semester, as well as the written final exam are required for completing the module.

Exercises

Regular exercises will consist of assignments distributed and discussed via OLAT or in class. Participation in and submission of the exercises is required for completing the course.

Final Exam

In order to be able to pass the module, you need to successfully participate in the exercises. The lecture is eventually completed by also passing the written final exam. Place and date are published in the UZH course catalogue and on OLAT (see links above).